SAP User Behavior Analytics for Security - Locus IT Services

SAP User Behavior Analytics for Security

Locus IT ServicesBehavioral AnalyticsSAP User Behavior Analytics for Security

SAP User Behavior Analytics for Security

ETM (Enterprise Threat Monitor) can automatically analyzes SAP Behavior Analytics usage patterns and allows SOC teams to classify and investigate incidents efficiently.

By using user behavior analysis, incidents can be distinguished from non-incidents efficiently. Behavioral analysis mainly focuses on understanding how consumers act and why, enabling accurate predictions about how they are likely to act in the future.

Behavioral analytics is a most recent advancement in business analytics that reveals new insights into the behavior of consumers on online games, e-Commerce platforms, web and mobile applications, and IoT.

The quicker increase in the volume of raw event data generated by the digital world enables methods that go beyond typical analysis by demographics and other traditional metrics that’ll tell us what kind of people took what actions in the previous days. It enables marketers to make the offers to the right consumer segments at the right time.

  • SAP Behavior Analytics uses the massive volumes of raw user event data captured during sessions in which consumers use game, application, or any website, including traffic data like navigation path, social media interactions,clicks, purchasing decisions and marketing responsiveness.
  • The data event includes advertising metrics like click-to-conversion time, as well as comparisons between other metrics like the monetary value of an order and the amount of time spent on the site.
  • These data points are then analyzed and compiled, whether by looking at session progression from when a user first entered the platform until a sale was made, or what other products user bought or looked at before purchasing. 

While business analytics has a more bigger focus on the who, what, where and when of business intelligence, behavioral analytics will narrows that scope, allowing one to take seemingly unrelated data points in order to predict and determine errors and future trends.

Detecting Suspicious Logons Using SAP Behavior Analytics

ETM (Enterprise Threat Monitor) keeps track of every workstations the users are using for accessing SAP systems. This allows building a base of user activity patterns based on user location.

By correlating this information ETM (Enterprise Threat Monitor) informs the security analyst if the originating activity is from an suspicious or unidentified workstation.

SAP Logon Anomaly

ETM (Enterprise Threat Monitor) continuously analyzes user activity and SAP Behavior Analytics patterns based on user login hours. When ETM detects any anomaly, it’ll informs the analyst by showing an exclamation mark near the event time, giving the user a hint that something may be suspicious.

By clicking on the details the analyst will receives information about the anomaly, based on user’s usual login patterns. ETM (Enterprise Threat Monitor) shows detailed information about the workstations that are used for accessing SAP systems. Additionally, ETM (Enterprise Threat Monitor) shows users which perform activity from the suspicious workstation.

  • Repudiate compromised credential attacks with risk based models that will validate user identity based on behavioral analysis.

Machine learning uses constraint-based and pattern matching algorithms. These techniques are unique for analyzing behavioral patterns of people signing in to systems that contain sensitive information. Compromised credentials are the destructive and most common type of information security breach. By applying ML to this challenge using a risk based model that will learns user behaviors over time is superior to many other intrusion detection methods being used today.

  • Streamline security access for the new employees along with 360 degree role based risk models that can be customized by IT for a specific needs.

Most CEO’s are worried about how poor user experiences can affect productivity. Multi-factor authentication workflows that have lower user performance can be improved with contextual insights based on more precise person based risk models.

As ML (machine learning) models learns the behaviors of employees related to access, user authentication accuracy will improves. By learning a range of approved patterns over time, ML (machine learning) can accelerate authorized employee access to systems and secure services.

Locus IT has worked with industries to implement, develop, and improve on their Analytics solution and helped them overcome their challenges using SAP products. We at Locus IT provide Behavior Analytics security as well as Behavior Analytics implementation, Behavior Analytics support, and Behavior Analytics migration. For more information please contact us.

Locus IT Project Management Office
What’s it?